Part of the solution. Bringing it all Together - Informa2on and Data Management

Transcription

1 Bringing it all Together - Informa2on and Data Management 1

2 Information vs. Data Information Knowledge, meaning The input needed to make business decisions The Focus Area of The Business Data Factual information Organized for analysis or optimised for system design & operation The Focus Area for IT Departments Information is trusted data put into a business context 2

3 Information Model vs Data Model! Information Model Data Model A formalized description of the information used by a business Shows the most important information objects Includes constraints imposed by business rules includes a complete description of each object i.e. Business Definitions How data is held within a system Contains constraints imposed to optimise the technical implementation Include attributes (i.e. lower level of detail) Multiple Data Models map to the same Information Model Shows relationship between information objects A model of the information requirements of the business How the Information Model is implemented in IT systems 3

4 Enterprise Information Management Information Management Set the strategy to enable delivery of trusted information to be used by the entire organization Set the strategy for how information is managed Planning, organizing, staffing, leading, and controlling Establish control over the information Organizing, retrieving, acquiring, integrating, maintaining information Strategy Data Governance Meet the demands of the Information Management strategy. Ensure effectiveness of data delivery Data is available, accessible, and has quality fit for purpose Ensure efficiency of data delivery Define processes for timely and efficient delivery of reusable data Delivery Treating Information and therefore data as an enterprise asset 4

5 Building Blocks Competitive World Class Advantage Customer Services 360 degree business view Trusted Information Master Data Management Data Governance ENABLES Process People Technology Common Information Model Other Data Master Data October 27,

6 Master Data and MDM Master Data Management Master Data Key data for the operation of the business Processes and tools to manage master data Core entities needed to conduct business, Aim: a unified view of each master data object Used by several functional groups and systems A single version of the truth for master data across an organization. objects Examples: customers, products, employees, material, suppliers etc. How? Identify authorised sources, or rules to achieve a Master Record Why does it need Managing? Exists in silos without coordination Reflects historical circumstances rather than current situation Integrate disparate master data sources Perform Matching, merging,cleansing, crossreferencing Identify and apply centralised DQ business rules Automate where possible Use workflow to resolve unclear cases link to data governance 6

7 The Logic behind Data Governance Need to make Business Decisions! Need trusted information This Requires TRUSTED DATA Most data still originates with humans. Governance is a way to raise the quality. Identify, measure, have clear processes to fix things. DG means putting people in charge of fixing and preventing issues with data so that the enterprise can become more efficient. TRUSTED DATA Has agreed definitions Has traceable origin Has good quality: Clean i.e. according to standards Not contain duplicates Is correctly integrated Achieved through Clear Ownership of data and definitions Clear responsibilities A clear process for decision making Centralised DQ business rules Established metrics and monitoring 7

8 Bringing it all Together Customer Interfacing Layer Business Intelligence Layer Demand Information Management Put people, processes, goals in place Assign Roles, Responsibilities, accountabilities Ensure alignment to the business strategic direction and KPI s Demand Supply Planning & Balancing Ensure common business information definition s (Information Model) Drive optimum business value Ensure efficient delivery of trusted information Straetgy Master Data Layer (Customer, Product, ) Master Data Management Systems, Data Sources Supply Data Governance People, processes, and technology required to deliver trusted data Formally manage data assets Assign accountability for data quality Put people in charge of fixing and preventing issues with data Use technology when necessary to aid the process. Delivery

9 With and Without Data Governance and MDM! Without Data cannot be trusted Business inflexibility and inefficiency Poor customer experience Incorrect business decisions Inefficient use of resources (effort spent on trial and error, investigation, workarounds) Dependence on a few key individuals With Data is trusted More confident, efficient business decisions Reduction of data management complexity & cost Reduced cost of errors based on bad data Less time for key resources spent chasing DQ issues Less dependency on individuals More reuse of data assets Can t find trusted data Can t make decisions Data is trusted Fragmented, nonintegrated data Don t want to reuse data New, trusted, well understood data is integrated Data is reused Create point to point solutions New data sources are certified and added 9

10 Implementation Tips Design Define your information model first Use the information model as a to guide the DG and MDM strategy. Which areas to start with Map system data to information areas Think Value Start small think big or even better think 'value : Find high impact areas i.e. Information area with most value, or most pain Incremental business value approach: Pick a quick win area to start demonstrating business value early Use this as Input to business case Use smaller business cases as springboards to expansion of MDM and improve overall DQ Set the Strategy Strategy comes before execution! The Information Management strategy in this case. Once that is defined, then define process, then people and technology Continuously assess performance against the strategy 10

11 Information Builders approach Information Builders leverage DG and MDM integration to enable BI since this is the same data being integrated. General quality benefits lead directly to BI benefits with trusted data. 11

12 Experts in IT Project Delivery 12

13 Our Focus: Business Value We are experts in IT project delivery. Our pragmatic approach ensures that our customers get the most business value from their IT solution. Our primary areas of expertise are: System Integration Data and Process Modelling CRM Business Process Management 13

14 Services Project Establishment Pre-study, requirements, project definition Project Implementation Technical Project Management, architecture, test management Software delivery Development, test, support Offshore development centre in Macedonia 14

15 Customers A selection of Polar Cape s customers in Sweden 15

16 Customer Cases 16

17 Reference Engagements (1 of 3) Information Modeling for Major international telco Polar Cape has been helping with the definition and implementation of a Common Information Model across the multiple business areas and countries. The objective is to improve communication between business areas, improve communication between business and IT, and to speed up the requirements gathering process Focus on active uptake of the model as a tool to improve quality and efficiency Long term objectives: Provide a foundation for DG and MDM Information and Process Modeling for software service provider In Q1 and Q Polar Cape will help one of it's new customers, a software service provider, to define their information and process models across their business. This business-driven exercise will enable the company to use a common language across the business units and systems and lay the foundation for future improvements in the IT system landscape. 17

18 Reference Engagements (2 of 3) Business Intelligence and Data Warehouse consolidation at international telecoms operator for major EDW consolidation Manager of business requirements Facilitator of more than 60 workshops together with all level 1-3 managers from the business and management consultants from the suppliers Part Responsible for RFP (business requirements, scope, and acceptance test procedures) Coordination of detailed Data Governance pre-study Strategies for Master Data Management and Data Governance 18

19 Reference Engagements (3 of 3) Implementation of a CRM and service fulfillment platform at major telecoms operator Services such as ADSL, LAN, IPTV and VoIP Rolled out in 7 countries CSR and self-service order entry Service fulfillment 19